Boru Douthwaite

Impact pathway evaluation: an approach for achieving and attributing impact in complex systems

Agricultural development is fundamentally a social process in which people construct solutions to their problems, often by modifying both new technologies and their own production systems to take advantage of new opportunities offered by the technologies. Hence, agricultural change is an immensely complex process, with a high degree of non-linearity. However, current best practice economic evaluation methods commonly used in the CGIAR system ignore complexity. In this paper we develop a two-stage monitoring, evaluation and impact assessment approach called impact pathway evaluation. This approach is based on program-theory evaluation from the field of evaluation, and the experience of the German development organization GTZ (Deutsche Gesellschaft fur Technische Zusammenarbeit GmbH). In the first stage of this approach, a research project develops an impact pathway for itself. which is an explicit theory or model of how the project sees itself achieving impact. The project then uses the impact pathway to guide project management in complex environments. The impact pathway may evolve, based on learning over time. The second stage is an ex post impact assessment sometime after the project has finished, in which the projects wider benefits are independently assessed. The evaluator seeks to establish plausible links between the project outputs and developmental changes, such as poverty alleviation. We illustrate the usefulness of impact pathway evaluation through examples from Nigeria and Indonesia

Blending "hard" and "soft" science: The "follow-the-technology" approach to catalyzing and evaluating technology change

The types of technology change catalyzed by research interventions in integrated natural resource management (INRM) are likely to require much more social negotiation and adaptation than are changes related to plant breeding, the dominant discipline within the system of the Consultative Group on International Agricultural Research (CGIAR). Conceptual models for developing and delivering high-yielding varieties have proven inadequate for delivering natural resource management (NRM) technologies that are adopted in farmers fields. Successful INRM requires tools and approaches that can blend the technical with the social, so that people from different disciplines and social backgrounds can effectively work and communicate with each other. This paper develops the follow-the-technology (FTT) approach to catalyzing, managing, and evaluating rural technology change as a framework that both hard and soft scientists can work with. To deal with complexity, INRM needs ways of working that are adaptive and flexible. The FTT approach uses technology as the entry point into a complex situation to determine what is important. In this way, it narrows the research arena to achievable boundaries. The methodology can also be used to catalyze technology change, both within and outside agriculture. The FTT approach can make it possible to channel the innovative potential of local people that is necessary in INRM to scale up from the pilot site to the landscape. The FTT approach is built on an analogy between technology change and Darwinian evolution, specifically between learning selection and natural selection. In learning selection, stakeholders experiment with a new technology and carry out the evolutionary roles of novelty generation, selection, and promulgation. The motivation to participate is a plausible promise made by the R&D team to solve a real farming problem. Case studies are presented from a spectrum of technologies to show that repeated learning selection cycles can result in an improvement in the performance of the plausible promise through adaptation and a sense of ownership by the stakeholders.

Understanding how participatory approaches foster innovation

Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting. The model is then used to analyse four participatory approaches and the model is evaluated through the quality of insights generated. It shows that, while outwardly very different, the four approaches are built from combinations of 11 strategies. Most of these strategies are aimed at providing information about new opportunities and deciding whether to adopt, and give less support to the other two processes, thus suggesting one way the four participatory approaches can be strengthened. Beyond analysing participatory approaches, the model could be used as a framework for diagnosing the health of local innovation systems and designing tailor-made approaches to strengthen them.

Contending with Complexity: The Role of Evaluation in Implementing Sustainable Natural Resource Management

Three case studies show that natural resource management (NRM) research aimed at sustainably improving the well-being of African small-holder farmers is complex, and that monitoring and evaluation (M&E) is an essential tool in coping with this complexity, supported by an ‘innovation systems’ view of the adoption process. In the case studies, researchers adjusted their activities and outputs on the basis of learning from M&E. Many of the insights came through identifying farmer innovations, which also proved a source of improvements to the respective technologies. Together, better understanding and iterative improvements made eventual widespread impact more likely. Farmers also learnt from M&E exercises and this learning facilitated adoption. The understanding of the early adoption process provided by M&E can provide a foundation for more plausible impact assessment.

Enabling the uptake of livestock–water productivity interventions in the crop–livestock systems of sub-Saharan Africa

Livestock–water productivity (LWP) refers to a set of innovations that could contribute towards reducing the amount of water needed per unit of output generated. But what does it take to get these ideas adopted by livestock keepers in crop–livestock systems? In this paper, we treat LWP as an innovation, and consider in what ways it may be introduced and/or developed among the crop–livestock agricultural systems by drawing on successful examples of change. In the first part of this paper, we introduce relevant tenets of the innovation systems literature, and introduce a three-component conceptual framework for the adoption of LWP technologies. In the second part, we describe three successful cases of resources use change. In the final section, we identify what we consider to be necessary components in successful change, and relate these to LWP. We argue that, in the under-regulated crop–livestock systems of eastern Africa, key areas for focus include social institutions, political systems, gender and leadership.

Enabling innovation: technology- and system-level approaches that capitalize on complexity.

we finish our training most of us believe that it is our job to conceptualize designs, develop products and worry little about what happens after they have been introduced. Our courses are generally too practical to bother with theories about how innovation occurs, who it affects and how we might better manage the process. Diesel, inventor of the diesel engine, distinguished between two phases in technological progress: the conception and carrying out of the idea, which is a happy period of creative mental work in which technical challenges are overcome, and the introduction of the innovation, which is a “struggle against stupidity and envy, apathy and evil, secret opposition and open conflict of interests, a horrible period of struggle with man, a martyrdom even if success ensues.” Diesel is perhaps overstating the difficulties of managing innovation, but nevertheless as engineers we are still taught to prefer technical “invention” and leave dealing with people and the “innovation” side to others. However, engineers ignore the innovation process at their peril. Enabling innovation means building on peoples’ ingenuity and motivations, rather than working against them. In this paper I describe the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. In the first part of the paper I describe the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. In the second part of the paper I look at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.

TRANSFORMING IMPACT ASSESSMENT: BEGINNING THE QUIET REVOLUTION OF INSTITUTIONAL LEARNING AND CHANGE

SUMMARY Scores of assessments of the impacts of agricultural research have been carried out over the years. However, few appear to have been used to improve decision making and the effectiveness of research programmes. The Institutional Learning and Change (ILAC) Initiative emerged within the Consultative Group on International Agricultural Research (CGIAR), with the goal of strengthening learning from experience and using lessons to improve pro-poor innovation. It is testing approaches for expanding the contributions of impact assessment and evaluation to learning, decision making and improvement.

Ecoregional research in Africa: learning lessons from IITA's Benchmark Area Approach

SUMMARY Ecoregional research has the potential to help address some of the huge challenges facing agriculture in developing countries by developing technologies that work under different agro-ecological conditions, and the processes by which these technologies can be adapted to work in other areas with similar conditions. The CGIAR system has been developing ecoregional research as a new paradigm for over a decade. In this paper we evaluate one of the most ambitious of these initiatives called the Benchmark Area Approach (BAA) pioneered by the International Institute of Tropical Agriculture. We evaluate the BAA against nine good practice criteria for ecoregional research and finding that the approach is delivering, or has the potential to deliver, on all nine. Many of the lessons learnt from this evaluation will be relevant to current and future attempts to undertake co-ordinated multi-locational research for development.